code: def get_model_creator(hparams):
      """Get the right model class depending on configuration."""
      if (
          hparams.encoder_type == "gnmt"
          or hparams.attention_architecture in ["gnmt", "gnmt_v2"]
      ):
          model_creator = gnmt_model.GNMTModel
      elif hparams.attention_architecture == "standard":
          model_creator = attention_model.AttentionModel
      elif not hparams.attention:
          model_creator = nmt_model.Model
      else:
          raise ValueError(
              "Unknown attention architecture %s"
              % hparams.attention_architecture
          )
      return model_creator
  
imports: from __future__ import print_function
  import math
  import os
  import random
  import time
  import tensorflow
  from .None import inference, gnmt_model
  from .gnmt import attention_model, model
  from .gnmt import model_helper
  from .gnmt.utils import nmt_utils, misc_utils
label_desc: Use image node_id 13 for calling a global function with example usage: get_model_creator(hparams) and returns: model_creator